Abstract
One health is a concept and an approach to promote the health of human and animal populations in a shared and healthy environment. This interdisciplinary endeavour requires collaboration across professions and a common language. Geographic epidemiology is concerned with the identification of spatial patterns of health related states and events in a population defined via the boundary of the study area. Such spatial patterns (trend, cluster and clustering) require clear definition to be meaningful in science communication. However, the term “disease cluster” has been defined in the literature in various and rather different ways. When geographic epidemiology is unable to make sense of its own concepts it is questionable how respective research results can benefit one health. The goal of this study is to clarify the concept of disease cluster within geographic epidemiology.
Examples of disease cluster definitions from the literature will be compared. The term disease cluster will be semantically distinguished from similar concepts: clustering, hot spot and outbreak. The epidemiological triangle of causation (agent, host and environment) will be used to conceptualize geographic epidemiological data analysis. The semantics and statistical meaning of expectation and prediction will be reviewed and play a key role.
The true meaning of a disease cluster will be identified as embedded within the well-known Besag-York-Mollié (BYM) regression model. All the spatial patterns identifiable from the BYM model will be conceptualized in a new paradigm: the geographic epidemiological trillium of causation.
The concept of a disease cluster is clarified and a definition proposed. The paradigm of the geographic epidemiological trillium will help guiding causal epidemiological research. And researchers will be equipped to ask more precise questions and communicate their results more clearly to those who need to know.